Motion sensors and specialized processing can be used to measure and classify the actions of persons or objects. For example, multiple sensors can be placed at body locations such as wrists, ankles, midsection, etc. By analyzing the motion measured by each sensor the subject's overall body movement or action can be determined.
Some sensor-based action recognition approaches utilize a single sensor while others use multiple sensors mounted in different locations to improve the accuracy of overall action recognition. Action recognition systems typically include feature extraction and classification processing that can be either distributed or centralized. However, conventional approaches may not have sufficient accuracy in recognizing the actions of a body or object for many modern applications.
Human action detection is useful in many applications such as medical-care monitoring, athlete training, teleimmersion, human-computer interaction, virtual reality, motion capture, etc. In some applications, such as medical care monitoring that takes place in a user's home, it may be desirable to maintain a low-cost system with a minimal number of sensors, and to reduce resource use such as processing power, bandwidth, cost, etc., while still maintaining desired accuracy and performance.